Web personalization can achieve two business goals: increased advertising revenue and increased sales revenue. The realization of the two goals is related to two kinds of user behavior: item sampling and item selection. Prior research does not provide a model of attitude formation toward a personalization agent nor of how attitudes relate to these two behaviors. This limits our understanding of how web personalization can be managed to increase advertising revenues and/or sales revenues. To fill this gap, the current research develops and tests a theoretical model of user attitudes and behaviors toward a personalization agent. The model is based on an integration of two theories: the elaboration likelihood model (ELM) and consumer search theory (CST). In the integrated model, a user’s attitude toward a personalization agent is influenced by both the number of items he/she has sampled so far (from CST) and the degree to which he/she cognitively processes each one (from ELM). In turn, attitude is modeled to influence both behaviors—that is, item selection and any further item sampling. We conducted a lab study and a field study to test six hypotheses. This research extends the theory on web personalization by providing a more complete picture of how sampling and processing of personalized recommendations influence a user’s attitude and behavior toward the personalization agent. For online merchants, this research highlights the trade-off between item sampling and item selection and provides practical guidance on how to steer users toward the attitudes and behaviors that will realize their business goals.